Modern fraud investigations rely heavily on digital forensics to recover evidence from computers, servers, mobile devices, and cloud databases. Forensics activities must utilize specialized software tooling to ensure data is extracted without altering system metadata or compromising evidence integrity.
  ┌────────────────────────────────────────────────────────┐
  │                 E-DISCOVERY INTEGRITY PIPELINE         │
  └───────────────────────────┬────────────────────────────┘
                              ▼
  ┌────────────────────────────────────────────────────────┐
  │   IDENTIFICATION   ──► Maps target data asset sources  │
  │   PRESERVATION     ──► Places strict system legal holds│
  │   COLLECTION       ──► Extracts forensic duplicates    │
  │   PROCESSING       ──► Normalizes and parses datasets  │
  └────────────────────────────────────────────────────────┘

The electronic discovery (e-Discovery) workflow follows a structured lifecycle:
  • Identification: Mapping the target data asset sources, including employee computers, corporate email servers, network storage volumes, and messaging platforms.
  • Preservation: Implementing strict data holds to prevent users from modifying or deleting relevant data files.
  • Collection: Extracting forensic duplicate copies of the target storage media using hardware write-blockers to protect metadata from alteration.
  • Processing: Normalizing the extracted datasets, removing duplicate files, indexing text data, and running targeted keyword queries to isolate relevant evidence for detail analysis.
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